Tierney, Heather L. R. and Pan, Bing (2009): A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries.
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A new area of research involves the use of Google data, which has been normalized and scaled to predict economic activity. In this paper, Poisson regressions are used to explore the relationship between the online traffic to a specific website and the search volumes for certain keyword search queries, along with the rankings of that specific website for those queries. Daily and weekly data are used to discuss the effects that normalization, scaling, and aggregation have on the empirical findings, which are frequency-dependent.
|Item Type:||MPRA Paper|
|Original Title:||A Poisson Regression Examination of the Relationship between Website Traffic and Search Engine Queries|
|Keywords:||Poisson Regression, Search Engine, Google Insights, Aggregation|
|Subjects:||C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C43 - Index Numbers and Aggregation
D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D83 - Search; Learning; Information and Knowledge; Communication; Belief
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C25 - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
|Depositing User:||Heather L.R. Tierney|
|Date Deposited:||06. Nov 2009 06:19|
|Last Modified:||12. Feb 2013 07:37|
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